Research On Human-computer Interaction Technology In Distributed Virtual Reality

Human-Computer Interaction(HCI)technology is one of the major issues that need to be solved in the computer field.Brain-Computer Interface(BCI)as a new type of human-computer interaction can achieve more natural and efficient interaction.With the rapid development of computer graphics and 5G technology,the widespread application of distributed virtual reality has been promoted.The combination of virtual reality and brain-computer interface technology provides effective solutions for the development of brain science and has important research significance.In order to effectively improve the classification accuracy of EEG signals,a motor imaging EEG signal classification method based on Wavelet Packet Transform(WPT)and Serial Parallel Convolutional Neural Network(SPCNN)is proposed.First,the wavelet packet transform algorithm is used to decompose the EEG signal in time and frequency,and the frequency band closely related to motor imagination is selected for reconstruction.The reconstructed EEG signal retains effective time-frequency information.Then,considering the characteristics between and within the different channels of the EEG signal,two convolution kernels of different sizes are designed to perform convolution operations respectively.Validated on the public competition data set BCI competition IV 2b,the average classification accuracy of 9 subjects reached 84.77%,which is better than traditional methods.In order to assist users in the training of motor-imaging brain signals,a multi-user virtual reality roaming system based on EEG is designed and developed.The experiment first trains the offline model,and then calls the model to classify the subject's signal in real time and transmit it to the system.The results proved that the subjects can roam in the virtual environment,and training can help the subjects The person outputs highquality EEG signals.Figure 44;Table 8;Reference 50...